Conformal multi-material mesh generation from labelled medical volumes (Dec 2012)

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1 Challenge the future

Conformal multi-material mesh generation from labelled medical volumes

2 Challenge the future

Introduction

• Generation of volume meshes for FEA

• Particular use case: hip prostheses analysis

• Typical pipeline:

Segmentation from patient’s CT-scan (a) to labelled volume image (b). Volume Meshing (c) of the image and FEA for stress-strain results (d,[Dick2011]).

3 Challenge the future

Introduction

• Mesh requirements:

• precise meshes

• segmentation-conform

• minimal mesh element number feature-adaptive

4 Challenge the future

Related Work

Weighted Delaunay Tetrahedralization refinement [Boltcheva2009]

Dynamic Particle System Meshing [Meyer2007]

Multi-labelled volumes meshes with particle systems [Meyer2008]

5 Challenge the future

Challenges

• long computation time • oversampling of edges and corners • no sharp-feature recreation ε-sample requirement

wrong topology, bad

reconstruction

too many samples

6 Challenge the future

Contribution

• Application of Integer Medial Axis (IMA) as fast, discrete

medial axis scheme

• proposal of local surface triangulation scheme for volume

images

7 Challenge the future

Integer Medial Axis - Analysis

8 Challenge the future

Integer Medial Axis - Idea

BioMesh3D – Centres of

maximal spheres

IMA – shortest path in feature

transform

9 Challenge the future

Integer Medial Axis – Results

Runtime

dataset BioMesh3D DeVIDE FE-Mesher

artificial 26 min 0.1 sec

Tooth 1h 41 min 1 sec

real femur 14h 11 min 2 sec

10 Challenge the future

Integer Medial Axis – Results

Quality

Tooth # Tetra 142795 DeVIDE FE-Mesher

Max. Min. Avg. Variance # bad

Tetra

%

bad

Aspect

Ratio

119.69 1.01 1.94 1.00 9282 6.50

Radius

Ratio

105.43 1.00 1.69 0.83 6736 4.72

Volume 272.34 0.0 2.96 21.74 0 0.0

Tooth # Tetra 118110 Simpleware FE+

Max. Min. Avg. Variance # bad

Tetra

%

bad

Aspect

Ratio

44.59 1.02 1.54 0.16 816 0.69

Radius

Ratio

921.55 1.00 1.37 7.92 997 0.84

Volume 46.68 0.0 3.41 14.24 0 0.0

14 Challenge the future

Integer Medial Axis – Results

Precision

16 Challenge the future

Minimal Sample for accurate Meshing Concept

• ε-sampling:

• ensures topologic conformity

• applies to dense and sparse

samples

• Loss of sharp features

• only applies for 3D meshes

without additional information

• our idea:

• mesh surface locally

• take surface mesh to

generate volume mesh

0,, xxBESx

17 Challenge the future

Minimal Sample for accurate Meshing Concept

1. Get TBN-Matrix per sample

vertex

2. Get Neighbourhood per

vertex

3. re-project points in

tangent plane

4. mesh via Local Delaunay

Triangulation tangent

plane neighbourhood

5. use established

connections in 3D

18 Challenge the future

Minimal Sample for accurate Meshing Results

VTK CGAL – no constraint CGAL – Convex Hull constraint

formation of holes due unsuitable Neighbourhood determination

19 Challenge the future

Conclusion and Future Work

• Improved runtime behaviour due to Medial Axis Transform

Algorithm change

• Local Triangulation in tangent space not ε-sample bound, but

dependent on Neighbourhood operation

• k-Nearest Neighbour not suitable for non-uniformal, sparse

samples

• In future: usage of natural neighbours for neighbourhood

determination